2025 (Current Year) Special graduate degree programs Specially Offered Degree Programs for Graduate Students Center of Data Science and Artificial Intelligence
Applied Practical Data Science and Artificial Intelligence 1A
- Academic unit or major
- Center of Data Science and Artificial Intelligence
- Instructor(s)
- Asako Kanezaki / Katsumi Nitta / Norio Tomii / Kei Miyazaki / Keiji Okumura / Jun Sakuma / Yoshihiro Miyake / Isao Ono / Hideaki Nishimoto / Kazuo Yagura / Tomoya Kodama / Jun Deguchi / Norihiro Ao / Shinichiro Uragami / Ryo Inokuchi / Soichiro Watanabe / Takayoshi Yokota / Yutaro Tachibana
- Class Format
- Lecture (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Tue
- Class
- -
- Course Code
- DSA.P411
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 1Q
- Syllabus updated
- Mar 19, 2025
- Language
- Japanese
Syllabus
Course overview and goals
The purpose of this class course is to understand the current status and state-of-the-art of social implementation of AI and data science technologies, and to examine the applicability and challenges of these technologies. In each class, lecturers from companies in various fields such as architecture, IT, finance, and materials will introduce case studies of technology and product development using data science and AI.
The goal is for students to gain a broad perspective of the real world by acquiring knowledge about the application of data science and AI technologies in a wide range of fields, and by explaining their considerations about social applications in their assigned reports.
Therefore, in addition to the seven class sessions, this course emphasizes dialogue with company lecturers, and in principle, students shall participate in the DS&AI Forum to be held face-to-face on the Ookayama campus in the afternoon of May 28, 2025.
Course description and aims
This course aims to develop ability of each student to be more successful in the real world with the consideration of social implementation of data science and artificial intelligence.
Student learning outcomes
実務経験と講義内容との関連 (又は実践的教育内容)
In this course, lecturers from Dai-ichi Life Insurance, Mitsui Fudosan, Kioxia, JERA, Mizuho Financial Technology, Takenaka Corporation, and Institute of Science Tokyo will lecture on problem solving techniques based on their practical experience.
Keywords
Data Science, Artificial Intelligence, Machine Learning, Finance, Semiconductor, AI & Law, electric power development, construction
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
This course is classified as a high-flex type, but can only be taken in designated classrooms in Ookayama and Suzukakedai.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | DX Promotion and Use of Data Science and AI in Life Insurance Companies | This lecture will provide a picture of how data science and AI can be used for DX promotion in life insurance companies, with examples. |
| Class 2 | Data Utilization in Mitsui Fudosan Group | Share marketing case studies utilizing data at LaLaport and Tokyo Dome City. Improve planning skills for data utilization. |
| Class 3 | R&D of AI in Kioxia | AI-applied in memory development/production and the concept of memory-centric generative AI |
| Class 4 | DXing of Justice, Trends in LegalTech, AI and Law | The presentation will cover legal fundamentals, DXing the judiciary, AI assisting legal work, legal challenges in AI, and more. |
| Class 5 | Next Generation Power Plants and the Future of Energy Optimization | The presentation will provide examples of the use of digital, AI, and mathematical models in businesses from the power generation business to the electricity market. |
| Class 6 | Financial AI and Data Analytics in Practice | Machine learning, statistical science and genetative AI are increasingly being used in banks and other financial institutions. This lecture will explain the characteristics and approaches of AI and data analytics in the financial domain. Grand challenges and issues to be addressed in the future will also be explained, focusing on the technical aspects. |
| Class 7 | Utilization of AI and Advanced Technologies in the Construction Industry | This lecture will explore how AI and other advanced technologies are being implemented in the construction industry through various case studies. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
Textbook(s)
None required.
Reference books, course materials, etc.
Materials will be provided on Science Tokyo LMS in advance.
Evaluation methods and criteria
No final exam will be given. The evaluation will be based on the reports of each assignment.
The evaluation will also include the results of participation in the DSAI Forum to be held on May 28, 2025.
Related courses
- XCO.T487 ： Fundamentals of data science
- XCO.T488 ： Exercises in fundamentals of data science
- XCO.T489 ： Fundamentals of artificial intelligence
- XCO.T490 ： Exercises in fundamentals of artificial intelligence
Prerequisites
Doctoral students must take DSA.P611 "Progressive Applied Practical Data Science and AI 1A".
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Asako Kanezaki, Katsumi Nitta, Norio Tomii
lecture_ap[at]dsai.isct.ac.jp
Office hours
Contact by e-mail in advance to schedule an appointment.
Other
・This class is a technical course that can be considered an entrepreneurship course. The GAs that this subject corresponds to are GA0M and GA1M.
・This course corresponds to Applied AI and Data Science C1 (XCO.T485-1), which was offered until FY2023. Students who had Applied AI and Data Science C1 as undergraduates should register for this course. Students who have taken Applied AI and Data Science C1 in graduate school may not take this course.